566 research outputs found
Solid waste mixtures combustion in a circulating fluidized Bed: emission properties of NOx, Dioxin, and Heavy Metals
To efficiently and environment friendly combust the domestic garbage, sludge, and swill waste fuels, five different fuels are prepared by mixing the waste fuels together with coal, and grass biomass at different mixing ratios, and finally those fuels were combusted in a circulating fluidized bed (CFB) reactor. The emission performances of NOx, dioxin, and heavy metal during the combustion tests are studied. The results showed that a stable furnace temperature can be reached at approximately 850 °C when combusting all studied mixed fuels, benefiting the thermal processes of sludge and domestic garbage and thus realizing the purpose of waste-to-fuel. In addition, the dioxin emissions are much lower than the emission standards, and NOx emissions could be reduced significantly by adjusting the ratio of waste fuels. However, the emissions of mercury, lead, and the combinations of chromium, tin, antimony, cupper and manganese components all exceeded the pollution control standard for hazardous wastes incineration, a further technology is required for heavy metal reductions to achieve the emission standards
Semantic Equivariant Mixup
Mixup is a well-established data augmentation technique, which can extend the
training distribution and regularize the neural networks by creating ''mixed''
samples based on the label-equivariance assumption, i.e., a proportional mixup
of the input data results in the corresponding labels being mixed in the same
proportion. However, previous mixup variants may fail to exploit the
label-independent information in mixed samples during training, which usually
contains richer semantic information. To further release the power of mixup, we
first improve the previous label-equivariance assumption by the
semantic-equivariance assumption, which states that the proportional mixup of
the input data should lead to the corresponding representation being mixed in
the same proportion. Then a generic mixup regularization at the representation
level is proposed, which can further regularize the model with the semantic
information in mixed samples. At a high level, the proposed semantic
equivariant mixup (sem) encourages the structure of the input data to be
preserved in the representation space, i.e., the change of input will result in
the obtained representation information changing in the same way. Different
from previous mixup variants, which tend to over-focus on the label-related
information, the proposed method aims to preserve richer semantic information
in the input with semantic-equivariance assumption, thereby improving the
robustness of the model against distribution shifts. We conduct extensive
empirical studies and qualitative analyzes to demonstrate the effectiveness of
our proposed method. The code of the manuscript is in the supplement.Comment: Under revie
Universal primers for HBV genome DNA amplification across subtypes: a case study for designing more effective viral primers
<p>Abstract</p> <p>Background</p> <p>The highly heterogenic characteristic of viruses is the major obstacle to efficient DNA amplification. Taking advantage of the large number of virus DNA sequences in public databases to select conserved sites for primer design is an optimal way to tackle the difficulties in virus genome amplification.</p> <p>Results</p> <p>Here we use hepatitis B virus as an example to introduce a simple and efficient way for virus primer design. Based on the alignment of HBV sequences in public databases and a program BxB in Perl script, our method selected several optimal sites for HBV primer design. Polymerase chain reaction showed that compared with the success rate of the most popular primers for whole genome amplification of HBV, one set of primers for full length genome amplification and four sets of walking primers showed significant improvement. These newly designed primers are suitable for most subtypes of HBV.</p> <p>Conclusion</p> <p>Researchers can extend the method described here to design universal or subtype specific primers for various types of viruses. The BxB program based on multiple sequence alignment not only can be used as a separate tool but also can be integrated in any open source primer design software to select conserved regions for primer design.</p
Efficient subspace skyline query based on user preference using MapReduce
Subspace skyline, as an important variant of skyline, has been widely applied for multiple-criteria decisions, business planning. With the development of mobile internet, subspace skyline query in mobile distributed environments has recently attracted considerable attention. However, efficiently obtaining the meaningful subset of skyline points in any subspace remains a challenging task in the current mobile internet. For more and more mobile applications, subspace skyline query on mobile units is usually limited by big data and wireless bandwidth. To address this issue, in this paper, we propose a system model that can support subspace skyline query in mobile distributed environment. An efficient algorithm for processing the Subspace Skyline Query using MapReduce (SSQ) is also presented which can obtain the meaningful subset of points from the full set of skyline points in any subspace. The SSQ algorithm divides a subspace skyline query into two processing phases: the preprocess phase and the query phase. The preprocess phase includes the pruning process and constructing index process which is designed to reduce network delay and response time. Additionally, the query phase provides two filtering methods, SQM-filtering and ε-filtering, to filter the skyline points according to user preference and reduce network cost. Extensive experiments on real and synthetic data are conducted and the experimental results indicate that our algorithm is much efficient, meanwhile, the pruning strategy can further improve the efficiency of the algorithm
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